Abstract

Abstract This study extends the investigation of the impact of midlatitude ocean–atmosphere interactions on the atmospheric circulation to the interannual timescale by incorporating SST variability in the tropical Pacific representative of observed conditions. Two perpetual January GCM simulations are performed to examine the changes in the low-frequency atmospheric variability brought about by the inclusion of an interactive slab mixed layer in midlatitudes, in particular the changes in the extratropical response to ENSO-like tropical 90-day mean SST anomalies. It is found that midlatitude coupling alters the spatial organization of the low-frequency variability in qualitatively the same manner (but not to the same extent) as tropical SST variability—namely, by selectively enhancing (in terms of amplitude, persistence, and/or frequency of occurrence) certain of the preexisting (natural) dominant modes without significantly modifying them or generating new ones. While tropical SST forcing results in a notable amplification of the Pacific–North American (PNA) mode of the model, midlatitude SST anomalies appear to favor the regional zonal index circulations in the eastern and western Pacific (through decreased thermal damping at the surface). As a result, the PNA response to ENSO-like tropical SST forcing is not reinforced but slightly weakened by the presence of interactions with the underlying mixed layer. On the other hand, coupling increases the persistence of the overall extratropical signal and causes it to acquire distinct Western Pacific–like features, thus improving its resemblance to the observed ENSO teleconnection pattern. The leading mode of covariability between the hemispheric atmospheric circulation and North Pacific SST qualitatively reproduces its observational counterpart, with the atmosphere leading by about one month and surface atmospheric variations consistent with the notion that the atmosphere is driving the ocean. This agreement suggests that, even on interannual timescales, two-way air–sea interactions and ocean dynamics do not play an essential role in establishing the large-scale spatial structure of this observed dominant mode of ocean–atmosphere interaction. In addition, the simulated patterns of covariability in this sector possess the same kind of interannual–intraseasonal duality exhibited by the observations. In the North Atlantic the model essentially recovers the results from Part I of this study.

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